Current progress in humanoid robotics is centered on optimizing vision-language-action (VLA) models, integrating multimodal data, and enhancing instruction comprehension as well as the ability to interpret human intent. Training relies heavily on world models, human video data, and VR-based remote training, with increasing emphasis on first-person perspectives to strengthen perception. While the ultimate goal is to achieve general-purpose humanoids, development remains constrained by significant challenges, leading Western and Chinese companies to pursue divergent technological pathways.
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Key Highlights:
Humanoid robotics focuses on optimizing vision-language-action (VLA) models and enhancing multimodal data integration.
Improving instruction comprehension and human intent interpretation is a core development area.
Training relies heavily on world models, human video data, and VR-based remote training, with growing emphasis on first-person perspectives.
The ultimate goal is to achieve general-purpose humanoids, but major technical challenges persist.
Western and Chinese companies are pursuing different technological pathways in response.
Table of Contents
1. Vision Models as the Core of Robotic Perception
Figure 1: Humanoid Robot Model Operation Framework
Figure 2: Training Data for Humanoid Robots
Table 1: Comparison of First-Person and Third-Person View Algorithms
Figure 3: Apple HAT Model Overview
Table 2: Summary of First-Person Datasets
2. Strategic Moves by Humanoid Robot Model Developers